Robustness of the filtered-x LMS algorithm: part 11: robustness enhancement by minimal regularization for norm bounded uncertainty
Fraanje, R., Elliott, S.J. and Verhaegen, M. (2007) Robustness of the filtered-x LMS algorithm: part 11: robustness enhancement by minimal regularization for norm bounded uncertainty. IEEE Transactions on Signal Processing, 55, (8), 4038-4047. (doi:10.1109/TSP.2007.896086).
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Description/Abstract
The relationship between the regularization methods proposed in the literature to increase the robustness of the filtered-X LMS (FXLMS) algorithm is discussed. It is shown that the existing methods are special cases of a more general robust FXLMS algorithm in which particular filters determine the type of regularization. Based on the analysis by Fraanje, Verhaegen, and Elliott [ldquorobustness of the filtered-X LMS algorithm - part I: necessary conditions for convergence and the asymptotic pseudospectrum of Toeplitz Matricesrdquo of this issue], regularization filters are designed that guarantee that the strictly positive real conditions for asymptotic convergence or noncritical behavior are just satisfied for all uncertain systems contained in a particular norm bounded set.
| Item Type: | Article |
|---|---|
| Additional Information: | |
| ISSNs: | 1053-587X (print) |
| Related URLs: | |
| Subjects: | Q Science > Q Science (General) T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | University Structure - Pre August 2011 > Institute of Sound and Vibration Research > Signal Processing and Control |
| Item ID: | 49556 |
| Date Deposited: | 15 Nov 2007 |
| Last Modified: | 02 Mar 2012 13:09 |
| Contributors: | Fraanje, R. (Author) Elliott, S.J. (Author) Verhaegen, M. (Author) |
| Date: | August 2007 |
| Additional Information: | |
| Status: | Published |
| URI: | http://eprints.soton.ac.uk/id/eprint/49556 |
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